Toward carbon peaking and neutralization The heterogeneous stochastic convergence of CO2 emissions and the role of digital inclusive finance

This article explores the dynamic distribution of city-level CO2 emissions from China's national and regional perspectives. For this, we apply a q-& sigma; stochastic convergence model to inspect the heterogeneous convergence trend of carbon emissions at different quantiles. A panel time-varying quantile regression model with a factor structure was employed to determine the absolute and conditional q-& beta; stochastic convergence of CO2 emissions and to examine the dynamic influence of digital inclusive finance on the convergence of carbon emissions. The results show (i) CO2 emissions exhibit a spatially imbalanced distribution pattern of being low in east and high in the west. The dynamic progression of carbon emissions in different areas presents huge differences in which Eastern, Central and Western China show insignificant and significant changes of distribution trending in CO2 emissions. (ii) Excluding the central region, country's CO2 emissions in eastern and western regions display dynamic q-& sigma; convergence and dynamic absolute q-& beta; convergence at different quantiles. In contrast, a conditional q-& beta; convergence of CO2 emissions in the whole country and each region is found across 5%-95% quantiles. (iii) At national and regional emissions, the dynamic q-& sigma; convergence, absolute and conditional q-& beta; convergence typically becomes more pronounced at mid-high quantile than at low quantile. (iv) Development of digital inclusive finance across the country and in Central and Western China generally facilitates carbon emissions convergence, but the opposite result for the eastern region. Finally, comprehensive finance growth, digital finance and low-carbon technological efforts can be a better fit for achieving dual-carbon goals.